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Chinese positioning, segmenting and identifying method in natural scene image

A natural scene image and recognition method technology, applied in the field of Chinese positioning, can solve the problem that the model is difficult to expand, and achieve the effect of removing the influence of background factors

Active Publication Date: 2017-10-27
厦门商集网络科技有限责任公司
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Problems solved by technology

However, this method often requires a large amount of manually labeled data for training, and it is difficult to directly extend the trained model to more other application scenarios.

Method used

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  • Chinese positioning, segmenting and identifying method in natural scene image
  • Chinese positioning, segmenting and identifying method in natural scene image

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Embodiment Construction

[0023] Such as figure 1 As shown, this embodiment provides a method for Chinese positioning, segmentation, and recognition in natural scene images. The process can be divided into the following steps:

[0024] 1) Preliminary text positioning of the original picture through the FASText model, and extraction of candidate text areas;

[0025] 2) By pre-segmenting the candidate text area;

[0026] 3) Recognize the single-word part of the pre-segmented text area, and perform further single-word segmentation and recognition for the field part.

[0027] Such as figure 2 As shown, the figure (a) is the original picture; step 1 uses the getCharSegmentation function of FASText to extract the candidate image area, and the extracted image is shown in figure (b); the pre-segmentation operation of step 2 is specifically to determine the Unicom extracted in step 1 Area, after removing some small interconnected areas (noise), the area that meets the aspect ratio of Chinese characters (close to 1:1)...

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Abstract

The invention provides a Chinese positioning, segmenting and identifying method in a natural scene image. Through a FASText model, an original picture is subjected to preliminary character positioning, a candidate character area is extracted, the candidate character area is pre-segmented, the separate word part of the pre-segmented character area is identified, and a field part can be subjected to further separate-word segmentation and identification. By use of the method, through the accurate extraction of character stroke characteristics and the powerful character identification ability of a deep residual neural network, a path tree method is combined to simply and effectively realize a purpose of Chinese positioning and identification, and the method can be applied to various natural scenes and does not need supervised training.

Description

Technical field [0001] The invention belongs to the technical field of image processing, and specifically relates to a method for Chinese positioning, segmentation and recognition in natural scene images. Background technique [0002] Text recognition in natural scenes is a very important visual detection target. The text in the image contains a lot of useful information, which is essential for the understanding and acquisition of visual content. There are many related text recognition applications, including road signs, license plates, bills, and so on. [0003] Generally speaking, traditional OCR technology is affected by the complex background of natural scenes, and it is difficult to correctly complete related tasks. On the whole, this type of task can be divided into two stages, text localization and recognition. Text positioning is the precise positioning of the text position in the image, which is mainly based on extracting relevant text features, such as MSERs, to disting...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/20G06K9/32G06K9/34
CPCG06V10/22G06V10/245G06V10/267
Inventor 陈凯韦建何建华周异黄征杜保发周文贵查宏远
Owner 厦门商集网络科技有限责任公司
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